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Decagon vs Vellum

A side-by-side comparison of two ai agents tools — pricing, integrations, and the trade-offs that matter — so you can pick the right fit fast.

Decagon compared with Vellum
FeatureDecagonVellum
CategoryAI AgentsAI Agents
PricingPaid · from Custom pricingPaid · from Custom pricing
Best forCustomer SupportDevelopers, Product Managers
Use casesResolving customer support tickets autonomously, Handling multi-turn customer conversations with AI, Reducing human handoff for routine support inquiriesTesting and evaluating prompts systematically, Building production-grade LLM applications, Iterating on AI agent workflows before deployment
IntegrationsZendesk, Intercom, SalesforceOpenAI API, Anthropic API, API
Rating
WebsiteVisit DecagonVisit Vellum

Decagon

AI agent platform for building autonomous customer support agents.

Pros

  • +Handles complex, multi-turn customer conversations autonomously
  • +Learns from existing support data to improve accuracy
  • +Reduces human handoff for routine and moderately complex inquiries

Cons

  • Setup requires training on existing support knowledge and data
  • Complex edge cases still benefit from human agent escalation

Vellum

Development platform for building, testing, and deploying production LLM agents.

Pros

  • +Provides systematic prompt testing and evaluation tools
  • +Helps teams iterate on agent workflows before production deployment
  • +Built specifically for production LLM application development

Cons

  • Most valuable for teams building and iterating on LLM apps regularly
  • Requires some technical setup to integrate into existing pipelines

Decagon vs Vellum FAQ

Is Decagon better than Vellum?
Neither is universally better — both are ai agents tools. Decagon (Paid, from Custom pricing) is a strong fit for Resolving customer support tickets autonomously, while Vellum (Paid, from Custom pricing) suits Testing and evaluating prompts systematically. Pick by your primary use-case and budget.
What is the main difference between Decagon and Vellum?
Decagon focuses on "AI agent platform for building autonomous customer support agents." whereas Vellum focuses on "Development platform for building, testing, and deploying production LLM agents.". Their pricing starts at Custom pricing and Custom pricing respectively.

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